{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据加载"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "UnicodeDecodeError",
     "evalue": "'utf-8' codec can't decode byte 0xfa in position 2: invalid start byte",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mUnicodeDecodeError\u001b[0m                        Traceback (most recent call last)",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._convert_tokens\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._convert_with_dtype\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._string_convert\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers._string_box_utf8\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-8' codec can't decode byte 0xfa in position 2: invalid start byte",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mUnicodeDecodeError\u001b[0m                        Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-2-b46b7295bfd0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m#数据加载\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdataset\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'SupplyChain.csv'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0mdataset\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision)\u001b[0m\n\u001b[1;32m    686\u001b[0m     )\n\u001b[1;32m    687\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 688\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    689\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    690\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    458\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    459\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 460\u001b[0;31m         \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparser\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    461\u001b[0m     \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    462\u001b[0m         \u001b[0mparser\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, nrows)\u001b[0m\n\u001b[1;32m   1196\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnrows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1197\u001b[0m         \u001b[0mnrows\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_validate_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"nrows\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnrows\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1198\u001b[0;31m         \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1199\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1200\u001b[0m         \u001b[0;31m# May alter columns / col_dict\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, nrows)\u001b[0m\n\u001b[1;32m   2155\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnrows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2156\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2157\u001b[0;31m             \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2158\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2159\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_first_chunk\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.read\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._read_low_memory\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._read_rows\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._convert_column_data\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._convert_tokens\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._convert_with_dtype\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._string_convert\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers._string_box_utf8\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-8' codec can't decode byte 0xfa in position 2: invalid start byte"
     ]
    }
   ],
   "source": [
    "#数据加载\n",
    "dataset=pd.read_csv('SupplyChain.csv')#这里是数据读取编码的问题  需要处理一下 \n",
    "dataset#'utf-8' codec can't decode byte 0xfa in position 2: invalid start byte  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type</th>\n",
       "      <th>Days for shipping (real)</th>\n",
       "      <th>Days for shipment (scheduled)</th>\n",
       "      <th>Benefit per order</th>\n",
       "      <th>Sales per customer</th>\n",
       "      <th>Delivery Status</th>\n",
       "      <th>Late_delivery_risk</th>\n",
       "      <th>Category Id</th>\n",
       "      <th>Category Name</th>\n",
       "      <th>Customer City</th>\n",
       "      <th>...</th>\n",
       "      <th>Order Zipcode</th>\n",
       "      <th>Product Card Id</th>\n",
       "      <th>Product Category Id</th>\n",
       "      <th>Product Description</th>\n",
       "      <th>Product Image</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Product Price</th>\n",
       "      <th>Product Status</th>\n",
       "      <th>shipping date (DateOrders)</th>\n",
       "      <th>Shipping Mode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DEBIT</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>91.250000</td>\n",
       "      <td>314.640015</td>\n",
       "      <td>Advance shipping</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0</td>\n",
       "      <td>2/3/2018 22:56</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TRANSFER</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>-249.089996</td>\n",
       "      <td>311.359985</td>\n",
       "      <td>Late delivery</td>\n",
       "      <td>1</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0</td>\n",
       "      <td>1/18/2018 12:27</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CASH</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>-247.779999</td>\n",
       "      <td>309.720001</td>\n",
       "      <td>Shipping on time</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>San Jose</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0</td>\n",
       "      <td>1/17/2018 12:06</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DEBIT</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>22.860001</td>\n",
       "      <td>304.809998</td>\n",
       "      <td>Advance shipping</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0</td>\n",
       "      <td>1/16/2018 11:45</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>PAYMENT</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>134.210007</td>\n",
       "      <td>298.250000</td>\n",
       "      <td>Advance shipping</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0</td>\n",
       "      <td>1/15/2018 11:24</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180514</th>\n",
       "      <td>CASH</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>Shipping on time</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>Fishing</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1004</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Field+%26+Stre...</td>\n",
       "      <td>Field &amp; Stream Sportsman 16 Gun Fire Safe</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0</td>\n",
       "      <td>1/20/2016 3:40</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180515</th>\n",
       "      <td>DEBIT</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>-613.770019</td>\n",
       "      <td>395.980011</td>\n",
       "      <td>Late delivery</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>Fishing</td>\n",
       "      <td>Bakersfield</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1004</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Field+%26+Stre...</td>\n",
       "      <td>Field &amp; Stream Sportsman 16 Gun Fire Safe</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0</td>\n",
       "      <td>1/19/2016 1:34</td>\n",
       "      <td>Second Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180516</th>\n",
       "      <td>TRANSFER</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>141.110001</td>\n",
       "      <td>391.980011</td>\n",
       "      <td>Late delivery</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>Fishing</td>\n",
       "      <td>Bristol</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1004</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Field+%26+Stre...</td>\n",
       "      <td>Field &amp; Stream Sportsman 16 Gun Fire Safe</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0</td>\n",
       "      <td>1/20/2016 21:00</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180517</th>\n",
       "      <td>PAYMENT</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>186.229996</td>\n",
       "      <td>387.980011</td>\n",
       "      <td>Advance shipping</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>Fishing</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1004</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Field+%26+Stre...</td>\n",
       "      <td>Field &amp; Stream Sportsman 16 Gun Fire Safe</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0</td>\n",
       "      <td>1/18/2016 20:18</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180518</th>\n",
       "      <td>PAYMENT</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>168.949997</td>\n",
       "      <td>383.980011</td>\n",
       "      <td>Shipping on time</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>Fishing</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1004</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Field+%26+Stre...</td>\n",
       "      <td>Field &amp; Stream Sportsman 16 Gun Fire Safe</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0</td>\n",
       "      <td>1/19/2016 18:54</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>180519 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Type  Days for shipping (real)  Days for shipment (scheduled)  \\\n",
       "0          DEBIT                         3                              4   \n",
       "1       TRANSFER                         5                              4   \n",
       "2           CASH                         4                              4   \n",
       "3          DEBIT                         3                              4   \n",
       "4        PAYMENT                         2                              4   \n",
       "...          ...                       ...                            ...   \n",
       "180514      CASH                         4                              4   \n",
       "180515     DEBIT                         3                              2   \n",
       "180516  TRANSFER                         5                              4   \n",
       "180517   PAYMENT                         3                              4   \n",
       "180518   PAYMENT                         4                              4   \n",
       "\n",
       "        Benefit per order  Sales per customer   Delivery Status  \\\n",
       "0               91.250000          314.640015  Advance shipping   \n",
       "1             -249.089996          311.359985     Late delivery   \n",
       "2             -247.779999          309.720001  Shipping on time   \n",
       "3               22.860001          304.809998  Advance shipping   \n",
       "4              134.210007          298.250000  Advance shipping   \n",
       "...                   ...                 ...               ...   \n",
       "180514          40.000000          399.980011  Shipping on time   \n",
       "180515        -613.770019          395.980011     Late delivery   \n",
       "180516         141.110001          391.980011     Late delivery   \n",
       "180517         186.229996          387.980011  Advance shipping   \n",
       "180518         168.949997          383.980011  Shipping on time   \n",
       "\n",
       "        Late_delivery_risk  Category Id   Category Name Customer City  ...  \\\n",
       "0                        0           73  Sporting Goods        Caguas  ...   \n",
       "1                        1           73  Sporting Goods        Caguas  ...   \n",
       "2                        0           73  Sporting Goods      San Jose  ...   \n",
       "3                        0           73  Sporting Goods   Los Angeles  ...   \n",
       "4                        0           73  Sporting Goods        Caguas  ...   \n",
       "...                    ...          ...             ...           ...  ...   \n",
       "180514                   0           45         Fishing      Brooklyn  ...   \n",
       "180515                   1           45         Fishing   Bakersfield  ...   \n",
       "180516                   1           45         Fishing       Bristol  ...   \n",
       "180517                   0           45         Fishing        Caguas  ...   \n",
       "180518                   0           45         Fishing        Caguas  ...   \n",
       "\n",
       "       Order Zipcode Product Card Id Product Category Id  Product Description  \\\n",
       "0                NaN            1360                  73                  NaN   \n",
       "1                NaN            1360                  73                  NaN   \n",
       "2                NaN            1360                  73                  NaN   \n",
       "3                NaN            1360                  73                  NaN   \n",
       "4                NaN            1360                  73                  NaN   \n",
       "...              ...             ...                 ...                  ...   \n",
       "180514           NaN            1004                  45                  NaN   \n",
       "180515           NaN            1004                  45                  NaN   \n",
       "180516           NaN            1004                  45                  NaN   \n",
       "180517           NaN            1004                  45                  NaN   \n",
       "180518           NaN            1004                  45                  NaN   \n",
       "\n",
       "                                            Product Image  \\\n",
       "0            http://images.acmesports.sports/Smart+watch    \n",
       "1            http://images.acmesports.sports/Smart+watch    \n",
       "2            http://images.acmesports.sports/Smart+watch    \n",
       "3            http://images.acmesports.sports/Smart+watch    \n",
       "4            http://images.acmesports.sports/Smart+watch    \n",
       "...                                                   ...   \n",
       "180514  http://images.acmesports.sports/Field+%26+Stre...   \n",
       "180515  http://images.acmesports.sports/Field+%26+Stre...   \n",
       "180516  http://images.acmesports.sports/Field+%26+Stre...   \n",
       "180517  http://images.acmesports.sports/Field+%26+Stre...   \n",
       "180518  http://images.acmesports.sports/Field+%26+Stre...   \n",
       "\n",
       "                                     Product Name Product Price  \\\n",
       "0                                    Smart watch     327.750000   \n",
       "1                                    Smart watch     327.750000   \n",
       "2                                    Smart watch     327.750000   \n",
       "3                                    Smart watch     327.750000   \n",
       "4                                    Smart watch     327.750000   \n",
       "...                                           ...           ...   \n",
       "180514  Field & Stream Sportsman 16 Gun Fire Safe    399.980011   \n",
       "180515  Field & Stream Sportsman 16 Gun Fire Safe    399.980011   \n",
       "180516  Field & Stream Sportsman 16 Gun Fire Safe    399.980011   \n",
       "180517  Field & Stream Sportsman 16 Gun Fire Safe    399.980011   \n",
       "180518  Field & Stream Sportsman 16 Gun Fire Safe    399.980011   \n",
       "\n",
       "       Product Status shipping date (DateOrders)   Shipping Mode  \n",
       "0                   0             2/3/2018 22:56  Standard Class  \n",
       "1                   0            1/18/2018 12:27  Standard Class  \n",
       "2                   0            1/17/2018 12:06  Standard Class  \n",
       "3                   0            1/16/2018 11:45  Standard Class  \n",
       "4                   0            1/15/2018 11:24  Standard Class  \n",
       "...               ...                        ...             ...  \n",
       "180514              0             1/20/2016 3:40  Standard Class  \n",
       "180515              0             1/19/2016 1:34    Second Class  \n",
       "180516              0            1/20/2016 21:00  Standard Class  \n",
       "180517              0            1/18/2016 20:18  Standard Class  \n",
       "180518              0            1/19/2016 18:54  Standard Class  \n",
       "\n",
       "[180519 rows x 53 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset=pd.read_csv('SupplyChain.csv',encoding='unicode_escape')#这样数据就读取进来了  \n",
    "dataset#字段太多了 50多个字段  我们需要找到我们有用的字段  有专门的文件解释字段  需要先了解清楚"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据探索"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "53\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Index(['Type', 'Days for shipping (real)', 'Days for shipment (scheduled)',\n",
       "       'Benefit per order', 'Sales per customer', 'Delivery Status',\n",
       "       'Late_delivery_risk', 'Category Id', 'Category Name', 'Customer City',\n",
       "       'Customer Country', 'Customer Email', 'Customer Fname', 'Customer Id',\n",
       "       'Customer Lname', 'Customer Password', 'Customer Segment',\n",
       "       'Customer State', 'Customer Street', 'Customer Zipcode',\n",
       "       'Department Id', 'Department Name', 'Latitude', 'Longitude', 'Market',\n",
       "       'Order City', 'Order Country', 'Order Customer Id',\n",
       "       'order date (DateOrders)', 'Order Id', 'Order Item Cardprod Id',\n",
       "       'Order Item Discount', 'Order Item Discount Rate', 'Order Item Id',\n",
       "       'Order Item Product Price', 'Order Item Profit Ratio',\n",
       "       'Order Item Quantity', 'Sales', 'Order Item Total',\n",
       "       'Order Profit Per Order', 'Order Region', 'Order State', 'Order Status',\n",
       "       'Order Zipcode', 'Product Card Id', 'Product Category Id',\n",
       "       'Product Description', 'Product Image', 'Product Name', 'Product Price',\n",
       "       'Product Status', 'shipping date (DateOrders)', 'Shipping Mode'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(len(dataset.columns))\n",
    "dataset.columns#一共有53个字段  下面是字段的名字   其中我们的目标是要将用户（客户ID）按照RFM模型 进行分类 划分成为8个层次"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5654     47\n",
       "5004     45\n",
       "10591    45\n",
       "5715     44\n",
       "3708     44\n",
       "         ..\n",
       "13486     1\n",
       "17887     1\n",
       "15952     1\n",
       "13905     1\n",
       "14375     1\n",
       "Name: Customer Id, Length: 20652, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset[\"Customer Id\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         20755\n",
       "1         19492\n",
       "2         19491\n",
       "3         19490\n",
       "4         19489\n",
       "          ...  \n",
       "180514     1005\n",
       "180515     9141\n",
       "180516      291\n",
       "180517     2813\n",
       "180518     7547\n",
       "Name: Customer Id, Length: 180519, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset[\"Customer Id\"]#数据好像有 180519个订单  但是用户是20652个"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Type                                  0\n",
       "Days for shipping (real)              0\n",
       "Days for shipment (scheduled)         0\n",
       "Benefit per order                     0\n",
       "Sales per customer                    0\n",
       "Delivery Status                       0\n",
       "Late_delivery_risk                    0\n",
       "Category Id                           0\n",
       "Category Name                         0\n",
       "Customer City                         0\n",
       "Customer Country                      0\n",
       "Customer Email                        0\n",
       "Customer Fname                        0\n",
       "Customer Id                           0\n",
       "Customer Lname                        8\n",
       "Customer Password                     0\n",
       "Customer Segment                      0\n",
       "Customer State                        0\n",
       "Customer Street                       0\n",
       "Customer Zipcode                      3\n",
       "Department Id                         0\n",
       "Department Name                       0\n",
       "Latitude                              0\n",
       "Longitude                             0\n",
       "Market                                0\n",
       "Order City                            0\n",
       "Order Country                         0\n",
       "Order Customer Id                     0\n",
       "order date (DateOrders)               0\n",
       "Order Id                              0\n",
       "Order Item Cardprod Id                0\n",
       "Order Item Discount                   0\n",
       "Order Item Discount Rate              0\n",
       "Order Item Id                         0\n",
       "Order Item Product Price              0\n",
       "Order Item Profit Ratio               0\n",
       "Order Item Quantity                   0\n",
       "Sales                                 0\n",
       "Order Item Total                      0\n",
       "Order Profit Per Order                0\n",
       "Order Region                          0\n",
       "Order State                           0\n",
       "Order Status                          0\n",
       "Order Zipcode                    155679\n",
       "Product Card Id                       0\n",
       "Product Category Id                   0\n",
       "Product Description              180519\n",
       "Product Image                         0\n",
       "Product Name                          0\n",
       "Product Price                         0\n",
       "Product Status                        0\n",
       "shipping date (DateOrders)            0\n",
       "Shipping Mode                         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#看看数据是否有缺失值\n",
    "dataset.isnull().sum()#从这里可以看出来 有缺失值 \n",
    "#Customer Lname 有8个缺失值   Customer Zipcode 有3个缺失值   Order Zipcode有155679个缺失值  Product Description有180519个缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         False\n",
       "1         False\n",
       "2         False\n",
       "3         False\n",
       "4         False\n",
       "          ...  \n",
       "180514    False\n",
       "180515    False\n",
       "180516    False\n",
       "180517    False\n",
       "180518    False\n",
       "Name: Customer Zipcode, Length: 180519, dtype: bool"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#数据有缺失值  但是怎么填充比较合适呢  需要对相应的数据进行 探索 然后做填充的方法\n",
    "# Customer Zipcode 是客户所在邮编   我觉得可以通过客户所在街道Customer Street来填充吧   毕竟同一个街道的话 邮编大概率是相同的\n",
    "temp_CZ=dataset['Customer Zipcode'].isnull()\n",
    "temp_CZ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([35704, 46440, 82511], dtype='int64')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_CZ[temp_CZ==True].index#这样就把缺失值所在索引给拿出来了 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35704    Elk Grove\n",
       "46440    Elk Grove\n",
       "82511     El Monte\n",
       "Name: Customer Street, dtype: object"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['Customer Street'][temp_CZ[temp_CZ==True].index]#这样就拿到了对应的索引所在街道 然后我们看看 Elk Grove 和 El Monte 的邮编是多少"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([35704, 46440], dtype='int64')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset[dataset['Customer Street']=='Elk Grove'].index#我是想通过dataset然后通过索引来找到Elk Grove的值  值找出来了两个 刚好就是确实的那两个"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9126 Wishing Expressway     122\n",
       "4388 Burning Goose Ridge    117\n",
       "4720 Noble Hills Wynd       116\n",
       "2878 Hazy Wagon  Thicket    113\n",
       "398 Emerald Grove           109\n",
       "                           ... \n",
       "8428 Blue Prairie Farm        1\n",
       "4691 Cinder Crest             1\n",
       "409 Iron Park                 1\n",
       "4696 Red Wharf                1\n",
       "8933 Dewy Quay                1\n",
       "Name: Customer Street, Length: 7458, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_cx=dataset['Customer Street'].value_counts()#对Customer Street进行一下探索\n",
    "temp_cx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_cx['Elk Grove']#太天真了 原来Elk Grove只有两个 刚好是缺失的那两个    要是不缺失 早就通过街道查出邮编了"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_cx['El Monte']#同样 这个这么这么巧  只有一个"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#对dataset['Customer Zipcode']采用众数填补\n",
    "dataset['Customer Zipcode'].fillna(dataset['Customer Zipcode'].mode()[0],inplace=True)\n",
    "dataset['Customer Zipcode'].isnull().sum()#填充完之后 就没有缺失值了"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,16))\n",
    "data=dataset\n",
    "sns.heatmap(data.corr(),annot=True)#把相关性可视化一下"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Type                                  0\n",
       "Days for shipping (real)              0\n",
       "Days for shipment (scheduled)         0\n",
       "Benefit per order                     0\n",
       "Sales per customer                    0\n",
       "Delivery Status                       0\n",
       "Late_delivery_risk                    0\n",
       "Category Id                           0\n",
       "Category Name                         0\n",
       "Customer City                         0\n",
       "Customer Country                      0\n",
       "Customer Email                        0\n",
       "Customer Fname                        0\n",
       "Customer Id                           0\n",
       "Customer Lname                        8\n",
       "Customer Password                     0\n",
       "Customer Segment                      0\n",
       "Customer State                        0\n",
       "Customer Street                       0\n",
       "Customer Zipcode                      0\n",
       "Department Id                         0\n",
       "Department Name                       0\n",
       "Latitude                              0\n",
       "Longitude                             0\n",
       "Market                                0\n",
       "Order City                            0\n",
       "Order Country                         0\n",
       "Order Customer Id                     0\n",
       "order date (DateOrders)               0\n",
       "Order Id                              0\n",
       "Order Item Cardprod Id                0\n",
       "Order Item Discount                   0\n",
       "Order Item Discount Rate              0\n",
       "Order Item Id                         0\n",
       "Order Item Product Price              0\n",
       "Order Item Profit Ratio               0\n",
       "Order Item Quantity                   0\n",
       "Sales                                 0\n",
       "Order Item Total                      0\n",
       "Order Profit Per Order                0\n",
       "Order Region                          0\n",
       "Order State                           0\n",
       "Order Status                          0\n",
       "Order Zipcode                    155679\n",
       "Product Card Id                       0\n",
       "Product Category Id                   0\n",
       "Product Description              180519\n",
       "Product Image                         0\n",
       "Product Name                          0\n",
       "Product Price                         0\n",
       "Product Status                        0\n",
       "shipping date (DateOrders)            0\n",
       "Shipping Mode                         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()#还有缺失值  但是感觉是无关紧要的值 都是object类型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 相关指标可视化探索"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sales per customer</th>\n",
       "      <th>Market</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>314.640015</td>\n",
       "      <td>Pacific Asia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>311.359985</td>\n",
       "      <td>Pacific Asia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>309.720001</td>\n",
       "      <td>Pacific Asia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>304.809998</td>\n",
       "      <td>Pacific Asia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>298.250000</td>\n",
       "      <td>Pacific Asia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180514</th>\n",
       "      <td>399.980011</td>\n",
       "      <td>Pacific Asia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180515</th>\n",
       "      <td>395.980011</td>\n",
       "      <td>Pacific Asia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180516</th>\n",
       "      <td>391.980011</td>\n",
       "      <td>Pacific Asia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180517</th>\n",
       "      <td>387.980011</td>\n",
       "      <td>Pacific Asia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180518</th>\n",
       "      <td>383.980011</td>\n",
       "      <td>Pacific Asia</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>180519 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Sales per customer        Market\n",
       "0               314.640015  Pacific Asia\n",
       "1               311.359985  Pacific Asia\n",
       "2               309.720001  Pacific Asia\n",
       "3               304.809998  Pacific Asia\n",
       "4               298.250000  Pacific Asia\n",
       "...                    ...           ...\n",
       "180514          399.980011  Pacific Asia\n",
       "180515          395.980011  Pacific Asia\n",
       "180516          391.980011  Pacific Asia\n",
       "180517          387.980011  Pacific Asia\n",
       "180518          383.980011  Pacific Asia\n",
       "\n",
       "[180519 rows x 2 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 对于销售额进行探索（对应 Sales per customer） # 按照不同的Market, Order Region \n",
    "# 按照不同的Category Name # 按照不同的时间维度（年，月，星期，小时）的趋势 # Product Price与Sales per customer 相关性如何\n",
    "#看一下 Market, Order Region 之间的关系 \n",
    "data[['Sales per customer','Market']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LATAM           51594\n",
       "Europe          50252\n",
       "Pacific Asia    41260\n",
       "USCA            25799\n",
       "Africa          11614\n",
       "Name: Market, dtype: int64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Market'].value_counts()#一共就只有5加超市"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'不同的market中的Sales'}, xlabel='Market'>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#基于market进行聚合\n",
    "market=data.groupby('Market')\n",
    "market['Sales per customer'].sum().sort_values(ascending=False).plot.bar(figsize=(12,6),title='不同的market中的Sales')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'不同的Order Region中的Sales'}, xlabel='Order Region'>"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#同理按照不同的 Order Region 进行聚合可视化\n",
    "Region=data.groupby('Order Region')\n",
    "Region['Sales per customer'].sum().sort_values(ascending=False).plot.bar(figsize=(12,6),title='不同的Order Region中的Sales')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'不同的Category Name中的Sales'}, xlabel='Category Name'>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Category Name也进行一下聚合操作\n",
    "cat=data.groupby('Category Name')\n",
    "cat['Sales per customer'].sum().sort_values(ascending=False).plot.bar(figsize=(12,6),title='不同的Category Name中的Sales')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'不同的Category Name中的Sales均值'}, xlabel='Category Name'>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cat['Sales per customer'].mean().sort_values(ascending=False).plot.bar(figsize=(12,6),title='不同的Category Name中的Sales均值')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2018-01-31 22:56:00', '2018-01-13 12:27:00',\n",
       "               '2018-01-13 12:06:00', '2018-01-13 11:45:00',\n",
       "               '2018-01-13 11:24:00', '2018-01-13 11:03:00',\n",
       "               '2018-01-13 10:42:00', '2018-01-13 10:21:00',\n",
       "               '2018-01-13 10:00:00', '2018-01-13 09:39:00',\n",
       "               ...\n",
       "               '2016-01-16 06:49:00', '2016-01-16 06:49:00',\n",
       "               '2016-01-16 06:28:00', '2016-01-16 06:07:00',\n",
       "               '2016-01-16 05:04:00', '2016-01-16 03:40:00',\n",
       "               '2016-01-16 01:34:00', '2016-01-15 21:00:00',\n",
       "               '2016-01-15 20:18:00', '2016-01-15 18:54:00'],\n",
       "              dtype='datetime64[ns]', name='order date (DateOrders)', length=180519, freq=None)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 按照不同的时间维度（年，月，星期，小时）的趋势\n",
    "temp=pd.DatetimeIndex(data['order date (DateOrders)'])\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type</th>\n",
       "      <th>Days for shipping (real)</th>\n",
       "      <th>Days for shipment (scheduled)</th>\n",
       "      <th>Benefit per order</th>\n",
       "      <th>Sales per customer</th>\n",
       "      <th>Delivery Status</th>\n",
       "      <th>Late_delivery_risk</th>\n",
       "      <th>Category Id</th>\n",
       "      <th>Category Name</th>\n",
       "      <th>Customer City</th>\n",
       "      <th>Customer Country</th>\n",
       "      <th>Customer Email</th>\n",
       "      <th>Customer Fname</th>\n",
       "      <th>Customer Id</th>\n",
       "      <th>Customer Lname</th>\n",
       "      <th>Customer Password</th>\n",
       "      <th>Customer Segment</th>\n",
       "      <th>Customer State</th>\n",
       "      <th>Customer Street</th>\n",
       "      <th>Customer Zipcode</th>\n",
       "      <th>Department Id</th>\n",
       "      <th>Department Name</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Market</th>\n",
       "      <th>Order City</th>\n",
       "      <th>Order Country</th>\n",
       "      <th>Order Customer Id</th>\n",
       "      <th>order date (DateOrders)</th>\n",
       "      <th>Order Id</th>\n",
       "      <th>Order Item Cardprod Id</th>\n",
       "      <th>Order Item Discount</th>\n",
       "      <th>Order Item Discount Rate</th>\n",
       "      <th>Order Item Id</th>\n",
       "      <th>Order Item Product Price</th>\n",
       "      <th>Order Item Profit Ratio</th>\n",
       "      <th>Order Item Quantity</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Order Item Total</th>\n",
       "      <th>Order Profit Per Order</th>\n",
       "      <th>Order Region</th>\n",
       "      <th>Order State</th>\n",
       "      <th>Order Status</th>\n",
       "      <th>Order Zipcode</th>\n",
       "      <th>Product Card Id</th>\n",
       "      <th>Product Category Id</th>\n",
       "      <th>Product Description</th>\n",
       "      <th>Product Image</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Product Price</th>\n",
       "      <th>Product Status</th>\n",
       "      <th>shipping date (DateOrders)</th>\n",
       "      <th>Shipping Mode</th>\n",
       "      <th>order_year</th>\n",
       "      <th>order_month</th>\n",
       "      <th>order_weekday</th>\n",
       "      <th>order_hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DEBIT</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>91.250000</td>\n",
       "      <td>314.640015</td>\n",
       "      <td>Advance shipping</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>Puerto Rico</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Cally</td>\n",
       "      <td>20755</td>\n",
       "      <td>Holloway</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>PR</td>\n",
       "      <td>5365 Noble Nectar Island</td>\n",
       "      <td>725.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Fitness</td>\n",
       "      <td>18.251453</td>\n",
       "      <td>-66.037056</td>\n",
       "      <td>Pacific Asia</td>\n",
       "      <td>Bekasi</td>\n",
       "      <td>Indonesia</td>\n",
       "      <td>20755</td>\n",
       "      <td>1/31/2018 22:56</td>\n",
       "      <td>77202</td>\n",
       "      <td>1360</td>\n",
       "      <td>13.110000</td>\n",
       "      <td>0.04</td>\n",
       "      <td>180517</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0.29</td>\n",
       "      <td>1</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>314.640015</td>\n",
       "      <td>91.250000</td>\n",
       "      <td>Southeast Asia</td>\n",
       "      <td>Java Occidental</td>\n",
       "      <td>COMPLETE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0</td>\n",
       "      <td>2/3/2018 22:56</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TRANSFER</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>-249.089996</td>\n",
       "      <td>311.359985</td>\n",
       "      <td>Late delivery</td>\n",
       "      <td>1</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>Puerto Rico</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Irene</td>\n",
       "      <td>19492</td>\n",
       "      <td>Luna</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>PR</td>\n",
       "      <td>2679 Rustic Loop</td>\n",
       "      <td>725.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Fitness</td>\n",
       "      <td>18.279451</td>\n",
       "      <td>-66.037064</td>\n",
       "      <td>Pacific Asia</td>\n",
       "      <td>Bikaner</td>\n",
       "      <td>India</td>\n",
       "      <td>19492</td>\n",
       "      <td>1/13/2018 12:27</td>\n",
       "      <td>75939</td>\n",
       "      <td>1360</td>\n",
       "      <td>16.389999</td>\n",
       "      <td>0.05</td>\n",
       "      <td>179254</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>-0.80</td>\n",
       "      <td>1</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>311.359985</td>\n",
       "      <td>-249.089996</td>\n",
       "      <td>South Asia</td>\n",
       "      <td>Rajastán</td>\n",
       "      <td>PENDING</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0</td>\n",
       "      <td>1/18/2018 12:27</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CASH</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>-247.779999</td>\n",
       "      <td>309.720001</td>\n",
       "      <td>Shipping on time</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>San Jose</td>\n",
       "      <td>EE. UU.</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Gillian</td>\n",
       "      <td>19491</td>\n",
       "      <td>Maldonado</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>CA</td>\n",
       "      <td>8510 Round Bear Gate</td>\n",
       "      <td>95125.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Fitness</td>\n",
       "      <td>37.292233</td>\n",
       "      <td>-121.881279</td>\n",
       "      <td>Pacific Asia</td>\n",
       "      <td>Bikaner</td>\n",
       "      <td>India</td>\n",
       "      <td>19491</td>\n",
       "      <td>1/13/2018 12:06</td>\n",
       "      <td>75938</td>\n",
       "      <td>1360</td>\n",
       "      <td>18.030001</td>\n",
       "      <td>0.06</td>\n",
       "      <td>179253</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>-0.80</td>\n",
       "      <td>1</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>309.720001</td>\n",
       "      <td>-247.779999</td>\n",
       "      <td>South Asia</td>\n",
       "      <td>Rajastán</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0</td>\n",
       "      <td>1/17/2018 12:06</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DEBIT</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>22.860001</td>\n",
       "      <td>304.809998</td>\n",
       "      <td>Advance shipping</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>EE. UU.</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Tana</td>\n",
       "      <td>19490</td>\n",
       "      <td>Tate</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>CA</td>\n",
       "      <td>3200 Amber Bend</td>\n",
       "      <td>90027.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Fitness</td>\n",
       "      <td>34.125946</td>\n",
       "      <td>-118.291016</td>\n",
       "      <td>Pacific Asia</td>\n",
       "      <td>Townsville</td>\n",
       "      <td>Australia</td>\n",
       "      <td>19490</td>\n",
       "      <td>1/13/2018 11:45</td>\n",
       "      <td>75937</td>\n",
       "      <td>1360</td>\n",
       "      <td>22.940001</td>\n",
       "      <td>0.07</td>\n",
       "      <td>179252</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0.08</td>\n",
       "      <td>1</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>304.809998</td>\n",
       "      <td>22.860001</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Queensland</td>\n",
       "      <td>COMPLETE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0</td>\n",
       "      <td>1/16/2018 11:45</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>PAYMENT</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>134.210007</td>\n",
       "      <td>298.250000</td>\n",
       "      <td>Advance shipping</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>Puerto Rico</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Orli</td>\n",
       "      <td>19489</td>\n",
       "      <td>Hendricks</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>PR</td>\n",
       "      <td>8671 Iron Anchor Corners</td>\n",
       "      <td>725.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Fitness</td>\n",
       "      <td>18.253769</td>\n",
       "      <td>-66.037048</td>\n",
       "      <td>Pacific Asia</td>\n",
       "      <td>Townsville</td>\n",
       "      <td>Australia</td>\n",
       "      <td>19489</td>\n",
       "      <td>1/13/2018 11:24</td>\n",
       "      <td>75936</td>\n",
       "      <td>1360</td>\n",
       "      <td>29.500000</td>\n",
       "      <td>0.09</td>\n",
       "      <td>179251</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0.45</td>\n",
       "      <td>1</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>298.250000</td>\n",
       "      <td>134.210007</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Queensland</td>\n",
       "      <td>PENDING_PAYMENT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>0</td>\n",
       "      <td>1/15/2018 11:24</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180514</th>\n",
       "      <td>CASH</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>Shipping on time</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>Fishing</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>EE. UU.</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Maria</td>\n",
       "      <td>1005</td>\n",
       "      <td>Peterson</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>NY</td>\n",
       "      <td>1322 Broad Glade</td>\n",
       "      <td>11207.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Fan Shop</td>\n",
       "      <td>40.640930</td>\n",
       "      <td>-73.942711</td>\n",
       "      <td>Pacific Asia</td>\n",
       "      <td>Shanghái</td>\n",
       "      <td>China</td>\n",
       "      <td>1005</td>\n",
       "      <td>1/16/2016 3:40</td>\n",
       "      <td>26043</td>\n",
       "      <td>1004</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>65177</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>Eastern Asia</td>\n",
       "      <td>Shanghái</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1004</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Field+%26+Stre...</td>\n",
       "      <td>Field &amp; Stream Sportsman 16 Gun Fire Safe</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0</td>\n",
       "      <td>1/20/2016 3:40</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180515</th>\n",
       "      <td>DEBIT</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>-613.770019</td>\n",
       "      <td>395.980011</td>\n",
       "      <td>Late delivery</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>Fishing</td>\n",
       "      <td>Bakersfield</td>\n",
       "      <td>EE. UU.</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Ronald</td>\n",
       "      <td>9141</td>\n",
       "      <td>Clark</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>CA</td>\n",
       "      <td>7330 Broad Apple Moor</td>\n",
       "      <td>93304.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Fan Shop</td>\n",
       "      <td>35.362545</td>\n",
       "      <td>-119.018700</td>\n",
       "      <td>Pacific Asia</td>\n",
       "      <td>Hirakata</td>\n",
       "      <td>Japón</td>\n",
       "      <td>9141</td>\n",
       "      <td>1/16/2016 1:34</td>\n",
       "      <td>26037</td>\n",
       "      <td>1004</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.01</td>\n",
       "      <td>65161</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>-1.55</td>\n",
       "      <td>1</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>395.980011</td>\n",
       "      <td>-613.770019</td>\n",
       "      <td>Eastern Asia</td>\n",
       "      <td>Osaka</td>\n",
       "      <td>COMPLETE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1004</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Field+%26+Stre...</td>\n",
       "      <td>Field &amp; Stream Sportsman 16 Gun Fire Safe</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0</td>\n",
       "      <td>1/19/2016 1:34</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180516</th>\n",
       "      <td>TRANSFER</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>141.110001</td>\n",
       "      <td>391.980011</td>\n",
       "      <td>Late delivery</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>Fishing</td>\n",
       "      <td>Bristol</td>\n",
       "      <td>EE. UU.</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>John</td>\n",
       "      <td>291</td>\n",
       "      <td>Smith</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>CT</td>\n",
       "      <td>97 Burning Landing</td>\n",
       "      <td>6010.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Fan Shop</td>\n",
       "      <td>41.629959</td>\n",
       "      <td>-72.967155</td>\n",
       "      <td>Pacific Asia</td>\n",
       "      <td>Adelaide</td>\n",
       "      <td>Australia</td>\n",
       "      <td>291</td>\n",
       "      <td>1/15/2016 21:00</td>\n",
       "      <td>26024</td>\n",
       "      <td>1004</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>65129</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0.36</td>\n",
       "      <td>1</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>391.980011</td>\n",
       "      <td>141.110001</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Australia del Sur</td>\n",
       "      <td>PENDING</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1004</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Field+%26+Stre...</td>\n",
       "      <td>Field &amp; Stream Sportsman 16 Gun Fire Safe</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0</td>\n",
       "      <td>1/20/2016 21:00</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180517</th>\n",
       "      <td>PAYMENT</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>186.229996</td>\n",
       "      <td>387.980011</td>\n",
       "      <td>Advance shipping</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>Fishing</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>Puerto Rico</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Mary</td>\n",
       "      <td>2813</td>\n",
       "      <td>Smith</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>PR</td>\n",
       "      <td>2585 Silent Autumn Landing</td>\n",
       "      <td>725.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Fan Shop</td>\n",
       "      <td>18.213350</td>\n",
       "      <td>-66.370575</td>\n",
       "      <td>Pacific Asia</td>\n",
       "      <td>Adelaide</td>\n",
       "      <td>Australia</td>\n",
       "      <td>2813</td>\n",
       "      <td>1/15/2016 20:18</td>\n",
       "      <td>26022</td>\n",
       "      <td>1004</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>0.03</td>\n",
       "      <td>65126</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0.48</td>\n",
       "      <td>1</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>387.980011</td>\n",
       "      <td>186.229996</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Australia del Sur</td>\n",
       "      <td>PENDING_PAYMENT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1004</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Field+%26+Stre...</td>\n",
       "      <td>Field &amp; Stream Sportsman 16 Gun Fire Safe</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0</td>\n",
       "      <td>1/18/2016 20:18</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180518</th>\n",
       "      <td>PAYMENT</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>168.949997</td>\n",
       "      <td>383.980011</td>\n",
       "      <td>Shipping on time</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>Fishing</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>Puerto Rico</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Andrea</td>\n",
       "      <td>7547</td>\n",
       "      <td>Ortega</td>\n",
       "      <td>XXXXXXXXX</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>PR</td>\n",
       "      <td>697 Little Meadow</td>\n",
       "      <td>725.0</td>\n",
       "      <td>7</td>\n",
       "      <td>Fan Shop</td>\n",
       "      <td>18.290380</td>\n",
       "      <td>-66.370613</td>\n",
       "      <td>Pacific Asia</td>\n",
       "      <td>Nagercoil</td>\n",
       "      <td>India</td>\n",
       "      <td>7547</td>\n",
       "      <td>1/15/2016 18:54</td>\n",
       "      <td>26018</td>\n",
       "      <td>1004</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>0.04</td>\n",
       "      <td>65113</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0.44</td>\n",
       "      <td>1</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>383.980011</td>\n",
       "      <td>168.949997</td>\n",
       "      <td>South Asia</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>PENDING_PAYMENT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1004</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Field+%26+Stre...</td>\n",
       "      <td>Field &amp; Stream Sportsman 16 Gun Fire Safe</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0</td>\n",
       "      <td>1/19/2016 18:54</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>180519 rows × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Type  Days for shipping (real)  Days for shipment (scheduled)  \\\n",
       "0          DEBIT                         3                              4   \n",
       "1       TRANSFER                         5                              4   \n",
       "2           CASH                         4                              4   \n",
       "3          DEBIT                         3                              4   \n",
       "4        PAYMENT                         2                              4   \n",
       "...          ...                       ...                            ...   \n",
       "180514      CASH                         4                              4   \n",
       "180515     DEBIT                         3                              2   \n",
       "180516  TRANSFER                         5                              4   \n",
       "180517   PAYMENT                         3                              4   \n",
       "180518   PAYMENT                         4                              4   \n",
       "\n",
       "        Benefit per order  Sales per customer   Delivery Status  \\\n",
       "0               91.250000          314.640015  Advance shipping   \n",
       "1             -249.089996          311.359985     Late delivery   \n",
       "2             -247.779999          309.720001  Shipping on time   \n",
       "3               22.860001          304.809998  Advance shipping   \n",
       "4              134.210007          298.250000  Advance shipping   \n",
       "...                   ...                 ...               ...   \n",
       "180514          40.000000          399.980011  Shipping on time   \n",
       "180515        -613.770019          395.980011     Late delivery   \n",
       "180516         141.110001          391.980011     Late delivery   \n",
       "180517         186.229996          387.980011  Advance shipping   \n",
       "180518         168.949997          383.980011  Shipping on time   \n",
       "\n",
       "        Late_delivery_risk  Category Id   Category Name Customer City  \\\n",
       "0                        0           73  Sporting Goods        Caguas   \n",
       "1                        1           73  Sporting Goods        Caguas   \n",
       "2                        0           73  Sporting Goods      San Jose   \n",
       "3                        0           73  Sporting Goods   Los Angeles   \n",
       "4                        0           73  Sporting Goods        Caguas   \n",
       "...                    ...          ...             ...           ...   \n",
       "180514                   0           45         Fishing      Brooklyn   \n",
       "180515                   1           45         Fishing   Bakersfield   \n",
       "180516                   1           45         Fishing       Bristol   \n",
       "180517                   0           45         Fishing        Caguas   \n",
       "180518                   0           45         Fishing        Caguas   \n",
       "\n",
       "       Customer Country Customer Email Customer Fname  Customer Id  \\\n",
       "0           Puerto Rico      XXXXXXXXX          Cally        20755   \n",
       "1           Puerto Rico      XXXXXXXXX          Irene        19492   \n",
       "2               EE. UU.      XXXXXXXXX        Gillian        19491   \n",
       "3               EE. UU.      XXXXXXXXX           Tana        19490   \n",
       "4           Puerto Rico      XXXXXXXXX           Orli        19489   \n",
       "...                 ...            ...            ...          ...   \n",
       "180514          EE. UU.      XXXXXXXXX          Maria         1005   \n",
       "180515          EE. UU.      XXXXXXXXX         Ronald         9141   \n",
       "180516          EE. UU.      XXXXXXXXX           John          291   \n",
       "180517      Puerto Rico      XXXXXXXXX           Mary         2813   \n",
       "180518      Puerto Rico      XXXXXXXXX         Andrea         7547   \n",
       "\n",
       "       Customer Lname Customer Password Customer Segment Customer State  \\\n",
       "0            Holloway         XXXXXXXXX         Consumer             PR   \n",
       "1                Luna         XXXXXXXXX         Consumer             PR   \n",
       "2           Maldonado         XXXXXXXXX         Consumer             CA   \n",
       "3                Tate         XXXXXXXXX      Home Office             CA   \n",
       "4           Hendricks         XXXXXXXXX        Corporate             PR   \n",
       "...               ...               ...              ...            ...   \n",
       "180514       Peterson         XXXXXXXXX      Home Office             NY   \n",
       "180515          Clark         XXXXXXXXX        Corporate             CA   \n",
       "180516          Smith         XXXXXXXXX        Corporate             CT   \n",
       "180517          Smith         XXXXXXXXX         Consumer             PR   \n",
       "180518         Ortega         XXXXXXXXX         Consumer             PR   \n",
       "\n",
       "                   Customer Street  Customer Zipcode  Department Id  \\\n",
       "0         5365 Noble Nectar Island             725.0              2   \n",
       "1                 2679 Rustic Loop             725.0              2   \n",
       "2             8510 Round Bear Gate           95125.0              2   \n",
       "3                  3200 Amber Bend           90027.0              2   \n",
       "4         8671 Iron Anchor Corners             725.0              2   \n",
       "...                            ...               ...            ...   \n",
       "180514            1322 Broad Glade           11207.0              7   \n",
       "180515       7330 Broad Apple Moor           93304.0              7   \n",
       "180516          97 Burning Landing            6010.0              7   \n",
       "180517  2585 Silent Autumn Landing             725.0              7   \n",
       "180518           697 Little Meadow             725.0              7   \n",
       "\n",
       "       Department Name   Latitude   Longitude        Market  Order City  \\\n",
       "0              Fitness  18.251453  -66.037056  Pacific Asia      Bekasi   \n",
       "1              Fitness  18.279451  -66.037064  Pacific Asia     Bikaner   \n",
       "2              Fitness  37.292233 -121.881279  Pacific Asia     Bikaner   \n",
       "3              Fitness  34.125946 -118.291016  Pacific Asia  Townsville   \n",
       "4              Fitness  18.253769  -66.037048  Pacific Asia  Townsville   \n",
       "...                ...        ...         ...           ...         ...   \n",
       "180514        Fan Shop  40.640930  -73.942711  Pacific Asia    Shanghái   \n",
       "180515        Fan Shop  35.362545 -119.018700  Pacific Asia    Hirakata   \n",
       "180516        Fan Shop  41.629959  -72.967155  Pacific Asia    Adelaide   \n",
       "180517        Fan Shop  18.213350  -66.370575  Pacific Asia    Adelaide   \n",
       "180518        Fan Shop  18.290380  -66.370613  Pacific Asia   Nagercoil   \n",
       "\n",
       "       Order Country  Order Customer Id order date (DateOrders)  Order Id  \\\n",
       "0          Indonesia              20755         1/31/2018 22:56     77202   \n",
       "1              India              19492         1/13/2018 12:27     75939   \n",
       "2              India              19491         1/13/2018 12:06     75938   \n",
       "3          Australia              19490         1/13/2018 11:45     75937   \n",
       "4          Australia              19489         1/13/2018 11:24     75936   \n",
       "...              ...                ...                     ...       ...   \n",
       "180514         China               1005          1/16/2016 3:40     26043   \n",
       "180515         Japón               9141          1/16/2016 1:34     26037   \n",
       "180516     Australia                291         1/15/2016 21:00     26024   \n",
       "180517     Australia               2813         1/15/2016 20:18     26022   \n",
       "180518         India               7547         1/15/2016 18:54     26018   \n",
       "\n",
       "        Order Item Cardprod Id  Order Item Discount  Order Item Discount Rate  \\\n",
       "0                         1360            13.110000                      0.04   \n",
       "1                         1360            16.389999                      0.05   \n",
       "2                         1360            18.030001                      0.06   \n",
       "3                         1360            22.940001                      0.07   \n",
       "4                         1360            29.500000                      0.09   \n",
       "...                        ...                  ...                       ...   \n",
       "180514                    1004             0.000000                      0.00   \n",
       "180515                    1004             4.000000                      0.01   \n",
       "180516                    1004             8.000000                      0.02   \n",
       "180517                    1004            12.000000                      0.03   \n",
       "180518                    1004            16.000000                      0.04   \n",
       "\n",
       "        Order Item Id  Order Item Product Price  Order Item Profit Ratio  \\\n",
       "0              180517                327.750000                     0.29   \n",
       "1              179254                327.750000                    -0.80   \n",
       "2              179253                327.750000                    -0.80   \n",
       "3              179252                327.750000                     0.08   \n",
       "4              179251                327.750000                     0.45   \n",
       "...               ...                       ...                      ...   \n",
       "180514          65177                399.980011                     0.10   \n",
       "180515          65161                399.980011                    -1.55   \n",
       "180516          65129                399.980011                     0.36   \n",
       "180517          65126                399.980011                     0.48   \n",
       "180518          65113                399.980011                     0.44   \n",
       "\n",
       "        Order Item Quantity       Sales  Order Item Total  \\\n",
       "0                         1  327.750000        314.640015   \n",
       "1                         1  327.750000        311.359985   \n",
       "2                         1  327.750000        309.720001   \n",
       "3                         1  327.750000        304.809998   \n",
       "4                         1  327.750000        298.250000   \n",
       "...                     ...         ...               ...   \n",
       "180514                    1  399.980011        399.980011   \n",
       "180515                    1  399.980011        395.980011   \n",
       "180516                    1  399.980011        391.980011   \n",
       "180517                    1  399.980011        387.980011   \n",
       "180518                    1  399.980011        383.980011   \n",
       "\n",
       "        Order Profit Per Order    Order Region        Order State  \\\n",
       "0                    91.250000  Southeast Asia    Java Occidental   \n",
       "1                  -249.089996      South Asia           Rajastán   \n",
       "2                  -247.779999      South Asia           Rajastán   \n",
       "3                    22.860001         Oceania         Queensland   \n",
       "4                   134.210007         Oceania         Queensland   \n",
       "...                        ...             ...                ...   \n",
       "180514               40.000000    Eastern Asia           Shanghái   \n",
       "180515             -613.770019    Eastern Asia              Osaka   \n",
       "180516              141.110001         Oceania  Australia del Sur   \n",
       "180517              186.229996         Oceania  Australia del Sur   \n",
       "180518              168.949997      South Asia         Tamil Nadu   \n",
       "\n",
       "           Order Status  Order Zipcode  Product Card Id  Product Category Id  \\\n",
       "0              COMPLETE            NaN             1360                   73   \n",
       "1               PENDING            NaN             1360                   73   \n",
       "2                CLOSED            NaN             1360                   73   \n",
       "3              COMPLETE            NaN             1360                   73   \n",
       "4       PENDING_PAYMENT            NaN             1360                   73   \n",
       "...                 ...            ...              ...                  ...   \n",
       "180514           CLOSED            NaN             1004                   45   \n",
       "180515         COMPLETE            NaN             1004                   45   \n",
       "180516          PENDING            NaN             1004                   45   \n",
       "180517  PENDING_PAYMENT            NaN             1004                   45   \n",
       "180518  PENDING_PAYMENT            NaN             1004                   45   \n",
       "\n",
       "        Product Description  \\\n",
       "0                       NaN   \n",
       "1                       NaN   \n",
       "2                       NaN   \n",
       "3                       NaN   \n",
       "4                       NaN   \n",
       "...                     ...   \n",
       "180514                  NaN   \n",
       "180515                  NaN   \n",
       "180516                  NaN   \n",
       "180517                  NaN   \n",
       "180518                  NaN   \n",
       "\n",
       "                                            Product Image  \\\n",
       "0            http://images.acmesports.sports/Smart+watch    \n",
       "1            http://images.acmesports.sports/Smart+watch    \n",
       "2            http://images.acmesports.sports/Smart+watch    \n",
       "3            http://images.acmesports.sports/Smart+watch    \n",
       "4            http://images.acmesports.sports/Smart+watch    \n",
       "...                                                   ...   \n",
       "180514  http://images.acmesports.sports/Field+%26+Stre...   \n",
       "180515  http://images.acmesports.sports/Field+%26+Stre...   \n",
       "180516  http://images.acmesports.sports/Field+%26+Stre...   \n",
       "180517  http://images.acmesports.sports/Field+%26+Stre...   \n",
       "180518  http://images.acmesports.sports/Field+%26+Stre...   \n",
       "\n",
       "                                     Product Name  Product Price  \\\n",
       "0                                    Smart watch      327.750000   \n",
       "1                                    Smart watch      327.750000   \n",
       "2                                    Smart watch      327.750000   \n",
       "3                                    Smart watch      327.750000   \n",
       "4                                    Smart watch      327.750000   \n",
       "...                                           ...            ...   \n",
       "180514  Field & Stream Sportsman 16 Gun Fire Safe     399.980011   \n",
       "180515  Field & Stream Sportsman 16 Gun Fire Safe     399.980011   \n",
       "180516  Field & Stream Sportsman 16 Gun Fire Safe     399.980011   \n",
       "180517  Field & Stream Sportsman 16 Gun Fire Safe     399.980011   \n",
       "180518  Field & Stream Sportsman 16 Gun Fire Safe     399.980011   \n",
       "\n",
       "        Product Status shipping date (DateOrders)   Shipping Mode  order_year  \\\n",
       "0                    0             2/3/2018 22:56  Standard Class        2018   \n",
       "1                    0            1/18/2018 12:27  Standard Class        2018   \n",
       "2                    0            1/17/2018 12:06  Standard Class        2018   \n",
       "3                    0            1/16/2018 11:45  Standard Class        2018   \n",
       "4                    0            1/15/2018 11:24  Standard Class        2018   \n",
       "...                ...                        ...             ...         ...   \n",
       "180514               0             1/20/2016 3:40  Standard Class        2016   \n",
       "180515               0             1/19/2016 1:34    Second Class        2016   \n",
       "180516               0            1/20/2016 21:00  Standard Class        2016   \n",
       "180517               0            1/18/2016 20:18  Standard Class        2016   \n",
       "180518               0            1/19/2016 18:54  Standard Class        2016   \n",
       "\n",
       "        order_month  order_weekday  order_hour  \n",
       "0                 1              2          22  \n",
       "1                 1              5          12  \n",
       "2                 1              5          12  \n",
       "3                 1              5          11  \n",
       "4                 1              5          11  \n",
       "...             ...            ...         ...  \n",
       "180514            1              5           3  \n",
       "180515            1              5           1  \n",
       "180516            1              4          21  \n",
       "180517            1              4          20  \n",
       "180518            1              4          18  \n",
       "\n",
       "[180519 rows x 57 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#取出  order date (DateOrders) 中的year month weekday hour\n",
    "data['order_year']=temp.year\n",
    "data['order_month']=temp.month\n",
    "data['order_weekday']=temp.weekday\n",
    "data['order_hour']=temp.hour\n",
    "data#data里面就添加出了几个字段 order_year\torder_month\torder_weekday\torder_hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'每小时的平均销售额'}, xlabel='order_hour'>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#对销售额进行探索  在不同的时间尺度\n",
    "plt.figure(figsize=(12,10))\n",
    "plt.subplot(2,2,1)\n",
    "df_year=data.groupby('order_year')#先按照order_year进行聚合\n",
    "df_year['Sales'].mean().plot(title='每年的平均销售额')\n",
    "\n",
    "plt.subplot(2,2,2)\n",
    "df_month=data.groupby('order_month')#先按照order_year进行聚合\n",
    "df_month['Sales'].mean().plot(title='每月的平均销售额')\n",
    "\n",
    "plt.subplot(2,2,3)\n",
    "df_weekday=data.groupby('order_weekday')#先按照order_year进行聚合\n",
    "df_weekday['Sales'].mean().plot(title='每周的平均销售额')\n",
    "\n",
    "plt.subplot(2,2,4)\n",
    "df_hour=data.groupby('order_hour')#先按照order_year进行聚合\n",
    "df_hour['Sales'].mean().plot(title='每小时的平均销售额')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 用户分层RFM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        2018-01-31 22:56:00\n",
       "1        2018-01-13 12:27:00\n",
       "2        2018-01-13 12:06:00\n",
       "3        2018-01-13 11:45:00\n",
       "4        2018-01-13 11:24:00\n",
       "                 ...        \n",
       "180514   2016-01-16 03:40:00\n",
       "180515   2016-01-16 01:34:00\n",
       "180516   2016-01-15 21:00:00\n",
       "180517   2016-01-15 20:18:00\n",
       "180518   2016-01-15 18:54:00\n",
       "Name: order date (DateOrders), Length: 180519, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#上面那个order date (DateOrders) 是 订单下单日期（精确到分钟，比如 1/31/2018 22:56） 先转成dataframe里面的标准格式\n",
    "data['order date (DateOrders)']=pd.to_datetime(data['order date (DateOrders)'])\n",
    "data['order date (DateOrders)']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2018-01-31 23:38:00')"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#这样转换以后可以看到 最后一笔订单的下单时间\n",
    "data['order date (DateOrders)'].max()#时间中的最大值就是最后一笔订单的下单时间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2018, 2, 1, 0, 0)"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#假设当前的时间是2018-2-1\n",
    "import datetime\n",
    "now=datetime.datetime(2018,2,1)\n",
    "now"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>order date (DateOrders)</th>\n",
       "      <th>Order Id</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Customer Id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>792</td>\n",
       "      <td>1</td>\n",
       "      <td>499.950012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>136</td>\n",
       "      <td>10</td>\n",
       "      <td>1819.730034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>229</td>\n",
       "      <td>18</td>\n",
       "      <td>3537.680094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>380</td>\n",
       "      <td>14</td>\n",
       "      <td>1719.630030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>457</td>\n",
       "      <td>7</td>\n",
       "      <td>1274.750023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20753</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>215.820007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20754</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>215.820007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20755</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>327.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20756</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11.540000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20757</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>39.750000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20652 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             order date (DateOrders)  Order Id        Sales\n",
       "Customer Id                                                \n",
       "1                                792         1   499.950012\n",
       "2                                136        10  1819.730034\n",
       "3                                229        18  3537.680094\n",
       "4                                380        14  1719.630030\n",
       "5                                457         7  1274.750023\n",
       "...                              ...       ...          ...\n",
       "20753                              0         1   215.820007\n",
       "20754                              0         1   215.820007\n",
       "20755                              0         1   327.750000\n",
       "20756                              0         1    11.540000\n",
       "20757                              0         1    39.750000\n",
       "\n",
       "[20652 rows x 3 columns]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#计算每个用户的RFM的指标\n",
    "customer_seg=data.groupby('Customer Id').agg({'order date (DateOrders)':lambda x:(now-x.max()).days,\n",
    "                                              'Order Id':lambda x:len(x),'Sales':lambda x:x.sum()\n",
    "                                             })\n",
    "customer_seg  #R最近一次消费时间间隔  F消费频率  M消费金额  就是下面准备的这三个字段 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R_value</th>\n",
       "      <th>F_value</th>\n",
       "      <th>M_value</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Customer Id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
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       "      <th>1</th>\n",
       "      <td>792</td>\n",
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       "      <td>499.950012</td>\n",
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       "      <td>10</td>\n",
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       "      <td>229</td>\n",
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       "      <td>3537.680094</td>\n",
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       "      <th>4</th>\n",
       "      <td>380</td>\n",
       "      <td>14</td>\n",
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       "      <th>5</th>\n",
       "      <td>457</td>\n",
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       "      <td>0</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20652 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             R_value  F_value      M_value\n",
       "Customer Id                               \n",
       "1                792        1   499.950012\n",
       "2                136       10  1819.730034\n",
       "3                229       18  3537.680094\n",
       "4                380       14  1719.630030\n",
       "5                457        7  1274.750023\n",
       "...              ...      ...          ...\n",
       "20753              0        1   215.820007\n",
       "20754              0        1   215.820007\n",
       "20755              0        1   327.750000\n",
       "20756              0        1    11.540000\n",
       "20757              0        1    39.750000\n",
       "\n",
       "[20652 rows x 3 columns]"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customer_seg.rename(columns={'order date (DateOrders)':'R_value','Order Id':'F_value','Sales':'M_value'},inplace=True)\n",
    "customer_seg#改个名字"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'R_value': {0.5: 159.0},\n",
       " 'F_value': {0.5: 7.0},\n",
       " 'M_value': {0.5: 1499.82503324}}"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#将RFM数据划分为2个尺度\n",
    "quantiles=customer_seg.quantile(q=[0.5])\n",
    "quantiles=quantiles.to_dict()\n",
    "quantiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "#R_value越小越好  对应的R_score就越大\n",
    "def R_Score(x,b,c):\n",
    "    if x<c[b][0.5]:\n",
    "        return 2\n",
    "    else :\n",
    "        return 1\n",
    "\n",
    "#F和M指标都是一样的 越大越好\n",
    "def RM_Score(x,b,c):\n",
    "    if x>c[b][0.5]:\n",
    "        return 2\n",
    "    else: \n",
    "        return 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>F_Score</th>\n",
       "      <th>M_Score</th>\n",
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       "    <tr>\n",
       "      <th>Customer Id</th>\n",
       "      <th></th>\n",
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       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>20756</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11.540000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>20757</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20652 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             R_value  F_value      M_value  R_Score  F_Score  M_Score\n",
       "Customer Id                                                          \n",
       "1                792        1   499.950012        1        1        1\n",
       "2                136       10  1819.730034        2        2        2\n",
       "3                229       18  3537.680094        1        2        2\n",
       "4                380       14  1719.630030        1        2        2\n",
       "5                457        7  1274.750023        1        1        1\n",
       "...              ...      ...          ...      ...      ...      ...\n",
       "20753              0        1   215.820007        2        1        1\n",
       "20754              0        1   215.820007        2        1        1\n",
       "20755              0        1   327.750000        2        1        1\n",
       "20756              0        1    11.540000        2        1        1\n",
       "20757              0        1    39.750000        2        1        1\n",
       "\n",
       "[20652 rows x 6 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#创建 R_Score,用于将R_value映射成[1,2]\n",
    "customer_seg['R_Score']=customer_seg['R_value'].apply(R_Score,args=('R_value',quantiles))\n",
    "customer_seg['F_Score']=customer_seg['F_value'].apply(RM_Score,args=('F_value',quantiles))\n",
    "customer_seg['M_Score']=customer_seg['M_value'].apply(RM_Score,args=('M_value',quantiles))\n",
    "customer_seg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "#计算RFM的分层\n",
    "def RFM_user(df):\n",
    "    if df['M_Score']==2 and df['F_Score']==2 and df['R_Score']==2:\n",
    "        return \"重要价值用户\"\n",
    "    if df['M_Score']==2 and df['F_Score']==1 and df['R_Score']==2:\n",
    "        return \"重要发展用户\" \n",
    "    if df['M_Score']==2 and df['F_Score']==2 and df['R_Score']==1:\n",
    "        return \"重要保持用户\"\n",
    "    if df['M_Score']==2 and df['F_Score']==1 and df['R_Score']==1:\n",
    "        return \"重要价值用户\"\n",
    "    \n",
    "    if df['M_Score']==1 and df['F_Score']==2 and df['R_Score']==2:\n",
    "        return \"一般价值用户\"\n",
    "    if df['M_Score']==1 and df['F_Score']==1 and df['R_Score']==2:\n",
    "        return \"一般发展用户\" \n",
    "    if df['M_Score']==1 and df['F_Score']==2 and df['R_Score']==1:\n",
    "        return \"一般保持用户\"\n",
    "    if df['M_Score']==1 and df['F_Score']==1 and df['R_Score']==1:\n",
    "        return \"一般价值用户\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>4</th>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>一般发展用户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20754</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>215.820007</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>一般发展用户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20755</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>327.750000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>一般发展用户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20756</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11.540000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>一般发展用户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20757</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>39.750000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>一般发展用户</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20652 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             R_value  F_value      M_value  R_Score  F_Score  M_Score  \\\n",
       "Customer Id                                                             \n",
       "1                792        1   499.950012        1        1        1   \n",
       "2                136       10  1819.730034        2        2        2   \n",
       "3                229       18  3537.680094        1        2        2   \n",
       "4                380       14  1719.630030        1        2        2   \n",
       "5                457        7  1274.750023        1        1        1   \n",
       "...              ...      ...          ...      ...      ...      ...   \n",
       "20753              0        1   215.820007        2        1        1   \n",
       "20754              0        1   215.820007        2        1        1   \n",
       "20755              0        1   327.750000        2        1        1   \n",
       "20756              0        1    11.540000        2        1        1   \n",
       "20757              0        1    39.750000        2        1        1   \n",
       "\n",
       "            Customer_Type  \n",
       "Customer Id                \n",
       "1                  一般价值用户  \n",
       "2                  重要价值用户  \n",
       "3                  重要保持用户  \n",
       "4                  重要保持用户  \n",
       "5                  一般价值用户  \n",
       "...                   ...  \n",
       "20753              一般发展用户  \n",
       "20754              一般发展用户  \n",
       "20755              一般发展用户  \n",
       "20756              一般发展用户  \n",
       "20757              一般发展用户  \n",
       "\n",
       "[20652 rows x 7 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customer_seg['Customer_Type']=customer_seg.apply(RFM_user,axis=1)\n",
    "customer_seg#这样就完成了用户的RFM分层"
   ]
  }
 ],
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